However, testing methods for early warning signals against historical
examples of transitions is susceptible to statistical mistakes that arise
from selecting data conditional on that data having already exhibited
a sudden transition. A central tenant of early warning theory is that
the system in question is slowly approaching a tipping point that lies
some unknown distance away. If nothing is done to remedy the situation,
this slow change will inevitably carry the system beyond the tipping
point, which introduces a sudden, rapid transition into an undesirable
state [1]}. This process can be described mathematically
as a bifurcation, in which a slowly changing parameter reaches
a critical value that causes the system stability to change.
